Hurricane Beryl made landfall near the island of Carriacou in St. Vincent and the Grenadines on Monday 1st July at approximately 15:00 UTC.
The map to the left shows the population changes for the most recent date and for the date of landfall.
The charts below, show the population changes for specific population centers.
Starting 2nd July almost no data was available for Carriacou, Petit Martinique, Union Island and Mayreau islands, indicating widespread electrical and connectivity outages.
Grenada island is seeing population continued population decreases in the north eastern half of the country and increases in inland and south western areas near the capital St. George’s.
Saint Vincent and the Grenadines continues to see a widespread population decrease in all areas.
This analysis is done using ‘Facebook Popluation Estimates’ data Meta’s Data for Good initiative. Analysis was conducted by IOM.
Limitations of this analysis include;
For more details, contact Brian Mc Donald bmcdonald@iom.int
As of 2nd July, there is a clear decrease in population in the north and eastern areas of Grenada island, while areas around and inland from the capital St. George’s, seeing population increases.
While the coastal area of St. George’s are still below the pre-crisis mean, the population has increased since 1st July.
Grenville, along with much of the eastern and northern areas of the island continue to see population decreases.
Almost no data was available on 2nd July for Carriacou, indicating widespread electrical and connectivity outages.
No data was available on 2nd July for Petit Martinique, indicating widespread electrical and connectivity outages.
No data was available on 2nd July for Union Island, indicating widespread electrical and connectivity outages.
No data was available on 2nd July for Mayreau, indicating widespread electrical and connectivity outages.
Of the 2,825 building footprints on Carricou Island, Grenada, imagery of an estimated 888 are currently covered by clouds, preventing analysis. Of the remaining 1,937 footprints, 57% show some degree of visible damage:
913 buildings (47.13%) with damage fraction between 0% and 20%
70 buildings (3.61%) with damage fraction between 20% and 40%
75 buildings (3.87%) with damage fraction between 40% and 60%
102 buildings (5.27%) with damage fraction between 60% and 80%
77 buildings (40.11%) with damage fraction between 80% and 100%
This analysis is provided courtesy of Microsoft AI for Good Lab, using imagery from Planet SkySat from 2nd July 2024.
damage_pct_0m – the fraction of the building footprint’s area that is classified as damaged by the model
damage_pct_10m – total damaged area within a 10m buffer of the building footprint (including the footprint itself) / building footprint’s area (this can be >1.0 but we clip to 1.0)
damage_pct_20m – same as above but with a 20m buffer
damage – 1 if damage_pct_0m > 0 else 0
unknown_pct– covered by clouds
This analysis uses optical satellite imagery and likely underestimates building damage as not all building damage can be detected from this visual perspective. Cloud cover prevented analysis of 31% of the buildings.